India’s pragmatic vaccination strategy against COVID-19: a mathematical modelling-based analysis
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Abstract
To investigate the impact of targeted vaccination strategies on morbidity and mortality due to COVID-19, as well as on the incidence of SARS-CoV-2, in India.
Design
Mathematical modelling.
Settings
Indian epidemic of COVID-19 and vulnerable population.
Data sources
Country-specific and age-segregated pattern of social contact, case fatality rate and demographic data obtained from peer-reviewed literature and public domain.
Model
An age-structured dynamical model describing SARS-CoV-2 transmission in India incorporating uncertainty in natural history parameters was constructed.
Interventions
Comparison of different vaccine strategies by targeting priority groups such as keyworkers including healthcare professionals, individuals with comorbidities (24–60 years old) and all above 60.
Main outcome measures
Incidence reduction and averted deaths in different scenarios, assuming that the current restrictions are fully lifted as vaccination is implemented.
Results
The priority groups together account for about 18% of India’s population. An infection-preventing vaccine with 60% efficacy covering all these groups would reduce peak symptomatic incidence by 20.6% (95% uncertainty intervals (UI) 16.7–25.4) and cumulative mortality by 29.7% (95% CrI 25.8–33.8). A similar vaccine with ability to prevent symptoms (but not infection) will reduce peak incidence of symptomatic cases by 10.4% (95% CrI 8.4–13.0) and cumulative mortality by 32.9% (95% CrI 28.6–37.3). In the event of insufficient vaccine supply to cover all priority groups, model projections suggest that after keyworkers, vaccine strategy should prioritise all who are >60 and subsequently individuals with comorbidities. In settings with weakest transmission, such as sparsely populated rural areas, those with comorbidities should be prioritised after keyworkers.
Conclusions
An appropriately targeted vaccination strategy would witness substantial mitigation of impact of COVID-19 in a country like India with wide heterogeneity. ‘Smart vaccination’, based on public health considerations, rather than mass vaccination, appears prudent.
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SciScore for 10.1101/2021.05.07.21256742: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:As with any modelling study, our analysis has limitations to note, which should be regarded as illustrating the importance of different factors for policy decisions, and not as a predictive framework. It is subject to various uncertainties, for example, the increased risk of death as a result of comorbidities. Further data on these excess risks will be valuable in refining our findings. In considering the key worker population, …
SciScore for 10.1101/2021.05.07.21256742: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:As with any modelling study, our analysis has limitations to note, which should be regarded as illustrating the importance of different factors for policy decisions, and not as a predictive framework. It is subject to various uncertainties, for example, the increased risk of death as a result of comorbidities. Further data on these excess risks will be valuable in refining our findings. In considering the key worker population, although we incorporated vaccination coverages consistent with the size of this population, we did not explicitly capture the broader societal impact of failing to vaccinate these individuals, another important area for future work. Finally, an important uncertainty relevant to our current work is the dynamics of immunity, whether induced by vaccination or by infection. For example, there is evidence that memory B-cells and neutralising antibodies persist at detectable levels in blood for months post-infection 24–26. Despite important recent advances in understanding implications for disease outcome upon reinfection 27, there remains much uncertainty, including on the role of the cellular immune response 28. A recent modelling study showed how immune mechanisms could mediate a decline in the severity of COVID-19 as it becomes endemic in the coming years 29, but it remains unclear how current licensed vaccines, in India and elsewhere, might shape these dynamics. Addressing these issues are beyond the scope of our current work, which focuses on the impli...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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